A modal approach for the evaluation of the response sensitivity of structural systems subjected to non-stationary random processes

Cacciola, Pierfrancesco; Colajanni, Piero; Muscolino, G.

doi:10.1016/j.cma.2004.11.006

Cited by 27 publications

(13 citation statements)

References 26 publications

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“…Ref. 33), by using Kronecker algebra 34 ; (ii) to approximate the mean-value and covariance vectors by means of thē rst-order interval Taylor series expansion; (iii) to derive the di®erential equations governing the evolution of the nominal value and¯rst-order sensitivity vectors of response statistics; (iv) to apply modal analysis in order to evaluate both the nominal value and the¯rst-order sensitivities of the mean-value and covariance vectors of the response 35 ; and (v) to compute the upper and lower bounds of the mean-value and covariance vectors by handy formulas.…”

Section: Introductionmentioning

confidence: 99%

Response Statistics of Linear Structures With Uncertain-but-Bounded Parameters Under Gaussian Stochastic Input

Muscolino

Sofi

2011

Int. J. Str. Stab. Dyn.

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Uncertainty plays a fundamental role in structural engineering since it may a®ect both external excitations and structural parameters. In this study, the analysis of linear structures with slight variations of the structural parameters subjected to stochastic excitation is addressed. It is realistically assumed that su±cient data are available to model the external excitation as a Gaussian random process, while only fragmentary or incomplete information about the structural parameters are known. Under this assumption, a nonprobabilistic approach is pursued and the°uctuating properties are modeled as uncertain-but-bounded parameters via interval analysis. A method for evaluating the lower and upper bounds of the second-order statistics of the response is presented. The proposed procedure basically consists in combining random vibration theory with¯rst-order interval Taylor series expansion of the mean-value and covariance vectors of the response. After some algebra, the sets of¯rst-order ordinary di®erential equations ruling the nominal and¯rst-order sensitivity vectors of response statistics are derived. Once such equations are solved, the bounds of the mean-value and covariance vectors of the response can be evaluated by handy formulas.To validate the procedure, numerical results concerning two di®erent structures with uncertain-but-bounded sti®ness properties under seismic excitation are presented.

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Section: Introductionmentioning

confidence: 99%

Response Statistics of Linear Structures With Uncertain-but-Bounded Parameters Under Gaussian Stochastic Input

Muscolino

Sofi

2011

Int. J. Str. Stab. Dyn.

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“…The first-order sensitivity of the deterministic response of the system is evaluated by means of the approach presented in Cacciola et al (2005). The standard sensitivity analysis entails the evaluation of the derivative of the response of the system with respect to significant system parameters, collected in the vector .…”

Section: Dynamic Response Sensitivity For Deterministic Loadmentioning

confidence: 99%

“…(35) For design purpose the non-dimensional sensitivity s n (2) (t) proposed in Cacciola et al (2005) given by the following equation…”

Section: Numerical Applicationmentioning

confidence: 99%

“…In this paper, the semi-analytical modal procedure proposed by Cacciola et al (2005), has been extended in order to consider multi-variate Gaussian stochastic load process. The method allows the evaluation of the sensitivity of the nodal response of large MDOF systems in the modal space corresponding to the nominal values.…”

Section: Introductionmentioning

confidence: 99%

“…Chaudhuri and Chakraborty (2004) determined the response sensitivity in the frequency domain of structures subjected to nonstationary seismic processes. Cacciola et al (2005) proposed a method to determine the sensitivity of second order statistics of linear structures forced by Gaussian excitation. Marano et al (2008) performed a parametric sensitivity analysis of the spectral response of a stochastic SDOF system subjected to a nonstationary seismic action with respect to uncertain soil parameters.…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of the stochastic response of structures coupled with vibrating barriers

Tombari

Zentner

Cacciola

2016

Probabilistic Engineering Mechanics

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The sensitivity of the stochastic response of linear behaving structures controlled by the novel Vibrating Barrier (ViBa) device is scrutinized. The Vibrating Barrier (ViBa) is a massive structure, hosted in the soil, calibrated for protecting structures by exploiting the structure-soilstructure interaction effect. Therefore the paper addresses the study of the sensitivity of soilstructure coupled systems in which the soil is modelled as a linear elastic medium with hysteretic damping. In order to accomplish efficient sensitivity analyses, a reduced model is determined by means of the Craig-Bampton procedure. Moreover, a lumped parameter model is used for converting the hysteretic damping soil model rigorously valid in the frequency domain to the approximately equivalent viscous damping model in order to perform conventional time-history analysis. The sensitivity is evaluated by determining a semi-analytical method based on the dynamic modification approach for the case of multi-variate stochastic input process. The ground motion is modelled as non-stationary zero-mean Gaussian random process defined by a given evolutionary Power Spectral Density function. The paper presents the sensitivity of the response statistics of a model of an industrial building, passively controlled by the ViBa, to relevant design parameters. Comparisons with pertinent Monte Carlo Simulation will show the effectiveness of the proposed approach.

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Sensitivity analysis of coupled acoustic-structural systems under non-stationary random excitations based on adjoint variable method

Shang

Zhai

Zhao

2021

Struct Multidisc Optim

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A modal approach for the evaluation of the response sensitivity of structural systems subjected to non-stationary random processes

Cited by 27 publications

References 26 publications

Response Statistics of Linear Structures With Uncertain-but-Bounded Parameters Under Gaussian Stochastic Input

Response Statistics of Linear Structures With Uncertain-but-Bounded Parameters Under Gaussian Stochastic Input

Sensitivity of the stochastic response of structures coupled with vibrating barriers

Sensitivity analysis of coupled acoustic-structural systems under non-stationary random excitations based on adjoint variable method

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